Compressed Sensing and Time-Parallel Reduced-Order Modeling for Structural Health Monitoring Using a DDDAS
暂无分享,去创建一个
[1] Jack Dongarra,et al. Computational Science — ICCS 2003 , 2003, Lecture Notes in Computer Science.
[2] Charbel Farhat,et al. Time‐decomposed parallel time‐integrators: theory and feasibility studies for fluid, structure, and fluid–structure applications , 2003 .
[3] Charbel Farhat,et al. Reduced-order fluid/structure modeling of a complete aircraft configuration , 2006 .
[4] Charbel Farhat,et al. On a data-driven environment for multiphysics applications , 2005, Future Gener. Comput. Syst..
[5] Gregory W. Brown,et al. Application of a three-field nonlinear fluid–structure formulation to the prediction of the aeroelastic parameters of an F-16 fighter , 2003 .
[6] F. Hemez,et al. Updating finite element dynamic models using an element-by-element sensitivity methodology , 1993 .
[7] Charbel Farhat,et al. Aeroelastic Dynamic Analysis of a Full F-16 Configuration for Various Flight Conditions , 2003 .
[8] Charbel Farhat,et al. Time‐parallel implicit integrators for the near‐real‐time prediction of linear structural dynamic responses , 2006 .
[9] F. Hemez,et al. Improved Damage Location Accuracy Using Strain Energy-Based Mode Selection Criteria , 1997 .
[10] Charbel Farhat,et al. DDEMA: A Data Driven Environment for Multiphysics Applications , 2003, International Conference on Computational Science.
[11] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[12] Leonidas J. Guibas,et al. Towards a Dynamic Data Driven System for Structural and Material Health Monitoring , 2006, International Conference on Computational Science.